Learning machine training based on plan types

A system for training a learning machine accesses a training database of reference metadata that describes reference plans that include reference first-type plans and reference second-type plans. Such plans may be travel plans or other plans. The system trains the learning machine to distinguish candidate first-type plans from candidate second-type plans. The training of the learning machine is based on a set of decision trees generated from randomly selected subsets of the reference metadata, and the randomly selected subsets each describe a corresponding randomly selected portion of the reference plans. The system then modifies the trained learning machine based on asymmetrical penalties for incorrectly distinguishing candidate first-type plans from candidate second-type plans. The system then provides the modified learning machine for run-time use in classifying plans.